Sentiments_Analyisis_for_Restaurant_Review.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/SauravBedse223/Sentiment_analyis_Restaurant_Reviews/blob/main/Sentiments_Analyisis_for_Restaurant_Review.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "a5655812",
      "metadata": {
        "id": "a5655812"
      },
      "source": [
        "Sentiments Analyisis for Restaurant Review"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "NRK4GE42rz7C",
      "metadata": {
        "id": "NRK4GE42rz7C",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "18846e7c-f943-4a9f-e1de-89c216ecde41"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f2b18ade",
      "metadata": {
        "id": "f2b18ade"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import classification_report, accuracy_score\n",
        "from transformers import BertTokenizer, BertForSequenceClassification, AdamW\n",
        "import torch\n",
        "from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler\n",
        "from tqdm import tqdm\n",
        "import matplotlib.pyplot as plt\n",
        "from wordcloud import WordCloud\n",
        "\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "\n",
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout, Conv1D, MaxPooling1D\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "Xms6hl9pqF7Y",
      "metadata": {
        "id": "Xms6hl9pqF7Y"
      },
      "outputs": [],
      "source": [
        "# Load and preprocess your restaurant reviews dataset (assuming you have a CSV file)\n",
        "df = pd.read_csv('/content/drive/MyDrive/IBM Skillbuild /Restaurant_Reviews_dataset.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "xewQeR5CnNtG",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "xewQeR5CnNtG",
        "outputId": "8e2ccf5f-7e1d-469a-d641-576f42b4041a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "\n",
        "# Plot the word cloud for positive and negative reviews\n",
        "positive_words = ' '.join(df[df['Liked'] == 1]['Review'].tolist())\n",
        "wordcloud_positive = WordCloud(width=800, height=400).generate(positive_words)\n",
        "\n",
        "negative_words = ' '.join(df[df['Liked'] == 0]['Review'].tolist())\n",
        "wordcloud_negative = WordCloud(width=800, height=400).generate(negative_words)\n",
        "\n",
        "plt.figure(figsize=(10, 5))\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.imshow(wordcloud_positive, interpolation='bilinear')\n",
        "plt.axis('off')\n",
        "plt.title('Positive Reviews')\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.imshow(wordcloud_negative, interpolation='bilinear')\n",
        "plt.axis('off')\n",
        "plt.title('Negative Reviews')\n",
        "\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "JzL70jJNp5vP",
      "metadata": {
        "id": "JzL70jJNp5vP"
      },
      "outputs": [],
      "source": [
        "# Split the dataset into training and testing sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(df['Review'], df['Liked'], test_size=0.2, random_state=42)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "3nrFMTZQqY95",
      "metadata": {
        "id": "3nrFMTZQqY95"
      },
      "source": [
        "##  Option 1: Traditional Machine Learning with TF-IDF features and Logistic Regression"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "VfwRPWiRqIOH",
      "metadata": {
        "id": "VfwRPWiRqIOH"
      },
      "outputs": [],
      "source": [
        "# Option 1: Traditional Machine Learning with TF-IDF features and Logistic Regression\n",
        "tfidf_vectorizer = TfidfVectorizer(max_features=5000)\n",
        "X_train_tfidf = tfidf_vectorizer.fit_transform(X_train)\n",
        "X_test_tfidf = tfidf_vectorizer.transform(X_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "H_jYxryvqIK_",
      "metadata": {
        "id": "H_jYxryvqIK_"
      },
      "outputs": [],
      "source": [
        "model_lr = LogisticRegression(max_iter=500)\n",
        "model_lr.fit(X_train_tfidf, y_train)\n",
        "y_pred_lr = model_lr.predict(X_test_tfidf)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "IHHLu0kRqIEY",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IHHLu0kRqIEY",
        "outputId": "5f9b5318-b062-456d-f3a4-088d3f1a5ade"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traditional Machine Learning (Logistic Regression) Results:\n",
            "Accuracy: 79.5 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.75      0.85      0.80        96\n",
            "           1       0.85      0.74      0.79       104\n",
            "\n",
            "    accuracy                           0.80       200\n",
            "   macro avg       0.80      0.80      0.79       200\n",
            "weighted avg       0.80      0.80      0.79       200\n",
            "\n"
          ]
        }
      ],
      "source": [
        "print(\"Traditional Machine Learning (Logistic Regression) Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_lr) * 100 ,'%')\n",
        "print(classification_report(y_test, y_pred_lr))\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Support Vector Machine model"
      ],
      "metadata": {
        "id": "gwg1Z4uXAdIp"
      },
      "id": "gwg1Z4uXAdIp"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "yx_QIu8Vpf2r",
      "metadata": {
        "id": "yx_QIu8Vpf2r",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5556c6bd-1d56-49a0-9e5b-0ae93c5ca804"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Support Vector Machine Results:\n",
            "Accuracy: 81.5 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.77      0.88      0.82        96\n",
            "           1       0.87      0.76      0.81       104\n",
            "\n",
            "    accuracy                           0.81       200\n",
            "   macro avg       0.82      0.82      0.81       200\n",
            "weighted avg       0.82      0.81      0.81       200\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Train and evaluate SVM\n",
        "svm_model = SVC(kernel='linear')\n",
        "svm_model.fit(X_train_tfidf, y_train)\n",
        "y_pred_svm = svm_model.predict(X_test_tfidf)\n",
        "print(\"Support Vector Machine Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_svm)* 100,'%')\n",
        "print(classification_report(y_test, y_pred_svm))"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Random Forest model"
      ],
      "metadata": {
        "id": "-MnMvw9GAmx7"
      },
      "id": "-MnMvw9GAmx7"
    },
    {
      "cell_type": "code",
      "source": [
        "# Train and evaluate Random Forest\n",
        "rf_model = RandomForestClassifier(n_estimators=100, random_state=42)\n",
        "rf_model.fit(X_train_tfidf, y_train)\n",
        "y_pred_rf = rf_model.predict(X_test_tfidf)\n",
        "print(\"Random Forest Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_rf)* 100,'%')\n",
        "print(classification_report(y_test, y_pred_rf))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iu1drqpK4jEr",
        "outputId": "5b34fb50-ea73-4b38-c02d-b3dc130931b7"
      },
      "id": "iu1drqpK4jEr",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Random Forest Results:\n",
            "Accuracy: 74.0 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.69      0.82      0.75        96\n",
            "           1       0.80      0.66      0.73       104\n",
            "\n",
            "    accuracy                           0.74       200\n",
            "   macro avg       0.75      0.74      0.74       200\n",
            "weighted avg       0.75      0.74      0.74       200\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Gradient Boosting model"
      ],
      "metadata": {
        "id": "aWPkWGqKApqS"
      },
      "id": "aWPkWGqKApqS"
    },
    {
      "cell_type": "code",
      "source": [
        "# Train and evaluate Gradient Boosting\n",
        "gb_model = GradientBoostingClassifier(n_estimators=100, learning_rate=0.1, random_state=42)\n",
        "gb_model.fit(X_train_tfidf, y_train)\n",
        "y_pred_gb = gb_model.predict(X_test_tfidf)\n",
        "print(\"Gradient Boosting Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_gb)* 100,'%')\n",
        "print(classification_report(y_test, y_pred_gb))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B08KJpCf4voI",
        "outputId": "7e296219-1dc5-4964-b13f-6e32adfb7f43"
      },
      "id": "B08KJpCf4voI",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Gradient Boosting Results:\n",
            "Accuracy: 71.5 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.67      0.80      0.73        96\n",
            "           1       0.78      0.63      0.70       104\n",
            "\n",
            "    accuracy                           0.71       200\n",
            "   macro avg       0.72      0.72      0.71       200\n",
            "weighted avg       0.73      0.71      0.71       200\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Naive Bayes model"
      ],
      "metadata": {
        "id": "ll42P2NoAszS"
      },
      "id": "ll42P2NoAszS"
    },
    {
      "cell_type": "code",
      "source": [
        "# Train and evaluate Naive Bayes\n",
        "nb_model = MultinomialNB()\n",
        "nb_model.fit(X_train_tfidf, y_train)\n",
        "y_pred_nb = nb_model.predict(X_test_tfidf)\n",
        "print(\"Naive Bayes Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_nb)* 100,'%')\n",
        "print(classification_report(y_test, y_pred_nb))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D3sUR58w4yy5",
        "outputId": "005e01a8-ee40-48f0-f7af-e100ac3b13ca"
      },
      "id": "D3sUR58w4yy5",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Naive Bayes Results:\n",
            "Accuracy: 79.0 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.75      0.85      0.80        96\n",
            "           1       0.84      0.73      0.78       104\n",
            "\n",
            "    accuracy                           0.79       200\n",
            "   macro avg       0.79      0.79      0.79       200\n",
            "weighted avg       0.80      0.79      0.79       200\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## LSTM model"
      ],
      "metadata": {
        "id": "lTemj-jsAwkM"
      },
      "id": "lTemj-jsAwkM"
    },
    {
      "cell_type": "code",
      "source": [
        "# Tokenize text data using Keras Tokenizer\n",
        "tokenizer = Tokenizer(num_words=5000)\n",
        "tokenizer.fit_on_texts(X_train)\n",
        "X_train_sequences = tokenizer.texts_to_sequences(X_train)\n",
        "X_test_sequences = tokenizer.texts_to_sequences(X_test)\n",
        "max_sequence_length = max([len(seq) for seq in X_train_sequences])\n",
        "X_train_pad = pad_sequences(X_train_sequences, maxlen=max_sequence_length, padding='post')\n",
        "X_test_pad = pad_sequences(X_test_sequences, maxlen=max_sequence_length, padding='post')"
      ],
      "metadata": {
        "id": "R5fDe6Ht41Nc"
      },
      "id": "R5fDe6Ht41Nc",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Train and evaluate LSTM model\n",
        "lstm_model = Sequential([\n",
        "    Embedding(input_dim=len(tokenizer.word_index)+1, output_dim=128, input_length=max_sequence_length),\n",
        "    LSTM(128),\n",
        "    Dense(1, activation='sigmoid')\n",
        "])\n",
        "lstm_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
        "history = lstm_model.fit(X_train_pad, y_train, epochs=10, batch_size=32, validation_data=(X_test_pad, y_test), verbose=2)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6wbfNV4f44Bb",
        "outputId": "d84bc433-5112-455b-c0bc-352f903bdd05"
      },
      "id": "6wbfNV4f44Bb",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "25/25 - 4s - loss: 0.6968 - accuracy: 0.5050 - val_loss: 0.6927 - val_accuracy: 0.5250 - 4s/epoch - 143ms/step\n",
            "Epoch 2/10\n",
            "25/25 - 1s - loss: 0.6931 - accuracy: 0.5200 - val_loss: 0.6939 - val_accuracy: 0.4800 - 1s/epoch - 47ms/step\n",
            "Epoch 3/10\n",
            "25/25 - 1s - loss: 0.6061 - accuracy: 0.6637 - val_loss: 0.6049 - val_accuracy: 0.7200 - 1s/epoch - 47ms/step\n",
            "Epoch 4/10\n",
            "25/25 - 1s - loss: 0.2500 - accuracy: 0.9137 - val_loss: 0.5164 - val_accuracy: 0.7100 - 1s/epoch - 49ms/step\n",
            "Epoch 5/10\n",
            "25/25 - 2s - loss: 0.0999 - accuracy: 0.9700 - val_loss: 0.7567 - val_accuracy: 0.7600 - 2s/epoch - 89ms/step\n",
            "Epoch 6/10\n",
            "25/25 - 2s - loss: 0.0517 - accuracy: 0.9812 - val_loss: 0.8441 - val_accuracy: 0.7950 - 2s/epoch - 81ms/step\n",
            "Epoch 7/10\n",
            "25/25 - 1s - loss: 0.0364 - accuracy: 0.9937 - val_loss: 1.4912 - val_accuracy: 0.7400 - 1s/epoch - 48ms/step\n",
            "Epoch 8/10\n",
            "25/25 - 1s - loss: 0.0488 - accuracy: 0.9850 - val_loss: 0.8897 - val_accuracy: 0.7900 - 1s/epoch - 47ms/step\n",
            "Epoch 9/10\n",
            "25/25 - 1s - loss: 0.0116 - accuracy: 0.9962 - val_loss: 1.0997 - val_accuracy: 0.7750 - 1s/epoch - 48ms/step\n",
            "Epoch 10/10\n",
            "25/25 - 1s - loss: 0.0044 - accuracy: 0.9987 - val_loss: 1.4491 - val_accuracy: 0.7450 - 1s/epoch - 48ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Evaluate the LSTM model on the test set\n",
        "loss, accuracy = lstm_model.evaluate(X_test_pad, y_test, verbose=0)\n",
        "print(\"LSTM model Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_nb)* 100,'%')\n",
        "print(classification_report(y_test, y_pred_nb))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vs-oTczUEXYi",
        "outputId": "63b5307f-a585-4aa1-b790-f00ba03fa75f"
      },
      "id": "Vs-oTczUEXYi",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "LSTM model Results:\n",
            "Accuracy: 79.0 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.75      0.85      0.80        96\n",
            "           1       0.84      0.73      0.78       104\n",
            "\n",
            "    accuracy                           0.79       200\n",
            "   macro avg       0.79      0.79      0.79       200\n",
            "weighted avg       0.80      0.79      0.79       200\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot accuracy and loss curves\n",
        "plt.plot(history.history['accuracy'], label='Training Accuracy')\n",
        "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
        "plt.title('Training and Validation Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "Jt9OYURW47wX",
        "outputId": "57709a50-5b25-4eec-b175-86bcefb822bc"
      },
      "id": "Jt9OYURW47wX",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(history.history['loss'], label='Training Loss')\n",
        "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
        "plt.title('Training and Validation Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "Jm-SQJWf5B14",
        "outputId": "d5d64c32-cc59-418c-ebc4-27f925e26e77"
      },
      "id": "Jm-SQJWf5B14",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Model names and their corresponding accuracies\n",
        "model_names = ['Logistic Regression', 'Support Vector Machine','Random Forest','Gradient Boosting model','Naive Bayes model','LSTM']\n",
        "accuracies = [79.5, 81.5, 74.0, 71.5, 79.0,79.0]  # Example accuracies (replace with your actual values)\n",
        "\n",
        "# Create a bar plot\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.bar(model_names, accuracies, color='skyblue')\n",
        "\n",
        "# Add titles and labels\n",
        "plt.title('Accuracy of Different Models')\n",
        "plt.xlabel('Models')\n",
        "plt.ylabel('Accuracy')\n",
        "\n",
        "# Display the plot\n",
        "plt.xticks(rotation=45)  # Rotate x-axis labels for better readability\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "L_IMiw_8CWXp",
        "outputId": "00742113-49a5-49ea-beb2-458629f6fabd"
      },
      "id": "L_IMiw_8CWXp",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "id": "A2erGmh5qx07",
      "metadata": {
        "id": "A2erGmh5qx07"
      },
      "source": [
        "## Option 2: Deep Learning with BERT"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "umjfoGtGqHPX",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336,
          "referenced_widgets": [
            "3d729c8746af42129fd399e49a32f3d8",
            "df9e03a539634f54849f583941a3f5eb",
            "31b4e8bf622b48dc99f37696d09fbda1",
            "26471973ed2c41c48a356efd916633c2",
            "00ccaeb20bbc4252b815ce8f3a2bff52",
            "8a5367c0c4964a72adedab1796b876e1",
            "11894bd0e346458d80fc25f71d96d486",
            "555fecc0fb0c45c782581af366fa8601",
            "26bcbd9952434e4891601952e49a9937",
            "86118ff05ed54a7ab0632d61d50edd82",
            "443da5e16f114fd3a5e613d5ba9dde5f",
            "371be1e984e94137a407366288516f5f",
            "091a9da8fce345e89ba6b4b91a6e9168",
            "62b50fe1902e489eb61de010d2ad3d29",
            "19b4854089734df9876aa1e6528768f9",
            "08bcdb84383f40f39c24ee245ebed3de",
            "3f5b4439ca4948f2a14b193cd97d98a3",
            "6cdf25454551427c8374b89c477dfeb2",
            "fbb69d076d49498bada1de91c1add214",
            "7f3ca94420d3409abb72ac7e3034e2ad",
            "4d46afedb9eb4f30911c0fe29a18d6f3",
            "85c03a9e61144264af7a488d16718d9d",
            "1a478dc53e3b4a098ceb02655efdda23",
            "bb23b63399ea4757866edaed9db23444",
            "f9b41a720da7447ab2fa238af5606e17",
            "261765a0fd3c4d2ebd11fa0b077e912a",
            "396c4ab5c5a74df08470149050e3ccd7",
            "36efe5c74d5e4a008346335a75a48b4e",
            "ddc7eaa727274c54933d3b6aaefc8c22",
            "f6f7cabe574d48ee82d8050ebda1fb5e",
            "9caf99f34f5b4d2abdfcf13a9d2b0620",
            "40fd23512aa14e7ea8b11cadec11cef1",
            "32764c5536ea44af926a8b22debf3c29",
            "0ef68e5a0d0f45eda17b55397a0e43aa",
            "088f0a466cc040b292fe1a654fb67bb7",
            "ceeb1431ea0f4440b95d877f23193022",
            "5011bbcad8af434591d2dd8e407497bd",
            "5e963a51825349e9b3f8f751026541d7",
            "44e577c6457d428d92a492e3c4dc5c2b",
            "08fd0c984c8942b496f6a5b0a3858704",
            "54c4e0abe6a74e39894d46ff82466af7",
            "aee9912f8eb2473ebd91797272951129",
            "c8848eadea3e4f989f8bcb784dd15c4d",
            "c8ec6468d8e04317b5670408423a204b",
            "053e679aa2f84da89df27acf635756c3",
            "661656641931453bb4abc8f02871587c",
            "3ef12a7e5aa14a259cbdb58b26b51cfa",
            "c5bfe4d98f1448a099f9e86b5abf8a6b",
            "8060f63ae62344d0a59c511ea10dfbc2",
            "c8821ac085994e5bb09bfa6bf462f769",
            "0c3e60e4d04d4078a67d458aa0c5ab82",
            "2ed64aa4191742209c7e151f4edb1940",
            "6895d0177ecf45ac9152eb45c31ad6d2",
            "1b2227c493554fe885e9b82ac1e44e86",
            "ad2fa234879b40fda987cb0a24b8bee9"
          ]
        },
        "id": "umjfoGtGqHPX",
        "outputId": "1721595e-b5ac-45e2-8a6b-cce542f8e546"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3d729c8746af42129fd399e49a32f3d8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "371be1e984e94137a407366288516f5f"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/466k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1a478dc53e3b4a098ceb02655efdda23"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/570 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "0ef68e5a0d0f45eda17b55397a0e43aa"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/440M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "053e679aa2f84da89df27acf635756c3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
          ]
        }
      ],
      "source": [
        "# Option 2: Deep Learning with BERT\n",
        "# Load the BERT tokenizer and model\n",
        "tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n",
        "model = BertForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "jhKrTTG5q0vf",
      "metadata": {
        "id": "jhKrTTG5q0vf"
      },
      "outputs": [],
      "source": [
        "# Tokenize and encode the text data\n",
        "def tokenize_text(texts, tokenizer, max_length=128):\n",
        "    input_ids = []\n",
        "    attention_masks = []\n",
        "\n",
        "    for text in tqdm(texts, desc=\"Tokenizing\"):\n",
        "        encoded_dict = tokenizer.encode_plus(\n",
        "            text,\n",
        "            add_special_tokens=True,\n",
        "            max_length=max_length,\n",
        "            pad_to_max_length=True,\n",
        "            return_attention_mask=True,\n",
        "            return_tensors='pt',\n",
        "            truncation=True\n",
        "        )\n",
        "\n",
        "        input_ids.append(encoded_dict['input_ids'])\n",
        "        attention_masks.append(encoded_dict['attention_mask'])\n",
        "\n",
        "    input_ids = torch.cat(input_ids, dim=0)\n",
        "    attention_masks = torch.cat(attention_masks, dim=0)\n",
        "\n",
        "    return input_ids, attention_masks"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "SGt4GW50q0qA",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SGt4GW50q0qA",
        "outputId": "a1aeb2a6-d7ce-478b-f4a2-8a8b694d75fc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Tokenizing:   0%|          | 0/800 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:2645: FutureWarning: The `pad_to_max_length` argument is deprecated and will be removed in a future version, use `padding=True` or `padding='longest'` to pad to the longest sequence in the batch, or use `padding='max_length'` to pad to a max length. In this case, you can give a specific length with `max_length` (e.g. `max_length=45`) or leave max_length to None to pad to the maximal input size of the model (e.g. 512 for Bert).\n",
            "  warnings.warn(\n",
            "Tokenizing: 100%|██████████| 800/800 [00:00<00:00, 1610.94it/s]\n",
            "Tokenizing: 100%|██████████| 200/200 [00:00<00:00, 1501.38it/s]\n"
          ]
        }
      ],
      "source": [
        "# Tokenize and encode training and testing data\n",
        "X_train_input_ids, X_train_attention_masks = tokenize_text(X_train, tokenizer)\n",
        "X_test_input_ids, X_test_attention_masks = tokenize_text(X_test, tokenizer)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2OJRY0Cgq0nM",
      "metadata": {
        "id": "2OJRY0Cgq0nM"
      },
      "outputs": [],
      "source": [
        "# Convert labels to tensors\n",
        "y_train = torch.tensor(y_train.values)\n",
        "y_test = torch.tensor(y_test.values)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "FijUvAiVrD48",
      "metadata": {
        "id": "FijUvAiVrD48"
      },
      "outputs": [],
      "source": [
        "# Create data loaders\n",
        "batch_size = 32\n",
        "train_data = TensorDataset(X_train_input_ids, X_train_attention_masks, y_train)\n",
        "train_sampler = RandomSampler(train_data)\n",
        "train_dataloader = DataLoader(train_data, sampler=train_sampler, batch_size=batch_size)\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "VqsoAIILrD0d",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VqsoAIILrD0d",
        "outputId": "7c30e81a-588f-4dd3-e59c-7214b7b12f51"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/optimization.py:429: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "# Training parameters\n",
        "epochs = 5\n",
        "learning_rate = 2e-5\n",
        "optimizer = AdamW(model.parameters(), lr=learning_rate)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "mZcv45HMrDww",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mZcv45HMrDww",
        "outputId": "016f12c5-afd6-4bce-a933-d5b49e347081"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/5 - Average Loss: 0.8286651396751403\n",
            "Epoch 2/5 - Average Loss: 0.4640677982568741\n",
            "Epoch 3/5 - Average Loss: 0.16617004334926605\n",
            "Epoch 4/5 - Average Loss: 0.06291328437626362\n",
            "Epoch 5/5 - Average Loss: 0.03681532334536314\n"
          ]
        }
      ],
      "source": [
        "# Training loop\n",
        "for epoch in range(epochs):\n",
        "    model.train()\n",
        "    total_loss = 0\n",
        "\n",
        "    for batch in train_dataloader:\n",
        "        b_input_ids, b_input_mask, b_labels = batch\n",
        "        optimizer.zero_grad()\n",
        "\n",
        "        outputs = model(b_input_ids, attention_mask=b_input_mask, labels=b_labels)\n",
        "        loss = outputs.loss\n",
        "        total_loss += loss.item()\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "\n",
        "    avg_loss = total_loss / len(train_dataloader)\n",
        "    print(f\"Epoch {epoch + 1}/{epochs} - Average Loss: {avg_loss}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "RVN3EWMdrSL1",
      "metadata": {
        "id": "RVN3EWMdrSL1"
      },
      "outputs": [],
      "source": [
        "# Evaluate the model on the test set\n",
        "model.eval()\n",
        "y_pred_bert = []\n",
        "\n",
        "test_data = TensorDataset(X_test_input_ids, X_test_attention_masks, y_test)\n",
        "test_sampler = SequentialSampler(test_data)\n",
        "test_dataloader = DataLoader(test_data, sampler=test_sampler, batch_size=batch_size)\n",
        "\n",
        "for batch in test_dataloader:\n",
        "    b_input_ids, b_input_mask, b_labels = batch\n",
        "    with torch.no_grad():\n",
        "        outputs = model(b_input_ids, attention_mask=b_input_mask)\n",
        "        logits = outputs.logits\n",
        "\n",
        "    y_pred_bert.extend(np.argmax(logits.cpu().numpy(), axis=1))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "KhSHnpsLrSB-",
      "metadata": {
        "id": "KhSHnpsLrSB-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ec00295b-8a5b-4bd6-c24e-702f4793bf58"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BERT Model Results:\n",
            "Accuracy: 96.5 %\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.94      0.99      0.96        96\n",
            "           1       0.99      0.94      0.97       104\n",
            "\n",
            "    accuracy                           0.96       200\n",
            "   macro avg       0.97      0.97      0.96       200\n",
            "weighted avg       0.97      0.96      0.97       200\n",
            "\n"
          ]
        }
      ],
      "source": [
        "print(\"BERT Model Results:\")\n",
        "print(\"Accuracy:\", accuracy_score(y_test, y_pred_bert) * 100,'%')\n",
        "print(classification_report(y_test, y_pred_bert))\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "S2BdvjYZBNgy"
      },
      "id": "S2BdvjYZBNgy"
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.13"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "3d729c8746af42129fd399e49a32f3d8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_df9e03a539634f54849f583941a3f5eb",
              "IPY_MODEL_31b4e8bf622b48dc99f37696d09fbda1",
              "IPY_MODEL_26471973ed2c41c48a356efd916633c2"
            ],
            "layout": "IPY_MODEL_00ccaeb20bbc4252b815ce8f3a2bff52"
          }
        },
        "df9e03a539634f54849f583941a3f5eb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_8a5367c0c4964a72adedab1796b876e1",
            "placeholder": "​",
            "style": "IPY_MODEL_11894bd0e346458d80fc25f71d96d486",
            "value": "tokenizer_config.json: 100%"
          }
        },
        "31b4e8bf622b48dc99f37696d09fbda1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_555fecc0fb0c45c782581af366fa8601",
            "max": 48,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_26bcbd9952434e4891601952e49a9937",
            "value": 48
          }
        },
        "26471973ed2c41c48a356efd916633c2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_86118ff05ed54a7ab0632d61d50edd82",
            "placeholder": "​",
            "style": "IPY_MODEL_443da5e16f114fd3a5e613d5ba9dde5f",
            "value": " 48.0/48.0 [00:00&lt;00:00, 1.72kB/s]"
          }
        },
        "00ccaeb20bbc4252b815ce8f3a2bff52": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8a5367c0c4964a72adedab1796b876e1": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "11894bd0e346458d80fc25f71d96d486": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "555fecc0fb0c45c782581af366fa8601": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "26bcbd9952434e4891601952e49a9937": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "86118ff05ed54a7ab0632d61d50edd82": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "443da5e16f114fd3a5e613d5ba9dde5f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "371be1e984e94137a407366288516f5f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_091a9da8fce345e89ba6b4b91a6e9168",
              "IPY_MODEL_62b50fe1902e489eb61de010d2ad3d29",
              "IPY_MODEL_19b4854089734df9876aa1e6528768f9"
            ],
            "layout": "IPY_MODEL_08bcdb84383f40f39c24ee245ebed3de"
          }
        },
        "091a9da8fce345e89ba6b4b91a6e9168": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_3f5b4439ca4948f2a14b193cd97d98a3",
            "placeholder": "​",
            "style": "IPY_MODEL_6cdf25454551427c8374b89c477dfeb2",
            "value": "vocab.txt: 100%"
          }
        },
        "62b50fe1902e489eb61de010d2ad3d29": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_fbb69d076d49498bada1de91c1add214",
            "max": 231508,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_7f3ca94420d3409abb72ac7e3034e2ad",
            "value": 231508
          }
        },
        "19b4854089734df9876aa1e6528768f9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4d46afedb9eb4f30911c0fe29a18d6f3",
            "placeholder": "​",
            "style": "IPY_MODEL_85c03a9e61144264af7a488d16718d9d",
            "value": " 232k/232k [00:00&lt;00:00, 2.56MB/s]"
          }
        },
        "08bcdb84383f40f39c24ee245ebed3de": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3f5b4439ca4948f2a14b193cd97d98a3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "6cdf25454551427c8374b89c477dfeb2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "fbb69d076d49498bada1de91c1add214": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7f3ca94420d3409abb72ac7e3034e2ad": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4d46afedb9eb4f30911c0fe29a18d6f3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "85c03a9e61144264af7a488d16718d9d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "1a478dc53e3b4a098ceb02655efdda23": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_bb23b63399ea4757866edaed9db23444",
              "IPY_MODEL_f9b41a720da7447ab2fa238af5606e17",
              "IPY_MODEL_261765a0fd3c4d2ebd11fa0b077e912a"
            ],
            "layout": "IPY_MODEL_396c4ab5c5a74df08470149050e3ccd7"
          }
        },
        "bb23b63399ea4757866edaed9db23444": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_36efe5c74d5e4a008346335a75a48b4e",
            "placeholder": "​",
            "style": "IPY_MODEL_ddc7eaa727274c54933d3b6aaefc8c22",
            "value": "tokenizer.json: 100%"
          }
        },
        "f9b41a720da7447ab2fa238af5606e17": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_f6f7cabe574d48ee82d8050ebda1fb5e",
            "max": 466062,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_9caf99f34f5b4d2abdfcf13a9d2b0620",
            "value": 466062
          }
        },
        "261765a0fd3c4d2ebd11fa0b077e912a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_40fd23512aa14e7ea8b11cadec11cef1",
            "placeholder": "​",
            "style": "IPY_MODEL_32764c5536ea44af926a8b22debf3c29",
            "value": " 466k/466k [00:00&lt;00:00, 20.9MB/s]"
          }
        },
        "396c4ab5c5a74df08470149050e3ccd7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "36efe5c74d5e4a008346335a75a48b4e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ddc7eaa727274c54933d3b6aaefc8c22": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "f6f7cabe574d48ee82d8050ebda1fb5e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9caf99f34f5b4d2abdfcf13a9d2b0620": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "40fd23512aa14e7ea8b11cadec11cef1": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "32764c5536ea44af926a8b22debf3c29": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "0ef68e5a0d0f45eda17b55397a0e43aa": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_088f0a466cc040b292fe1a654fb67bb7",
              "IPY_MODEL_ceeb1431ea0f4440b95d877f23193022",
              "IPY_MODEL_5011bbcad8af434591d2dd8e407497bd"
            ],
            "layout": "IPY_MODEL_5e963a51825349e9b3f8f751026541d7"
          }
        },
        "088f0a466cc040b292fe1a654fb67bb7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_44e577c6457d428d92a492e3c4dc5c2b",
            "placeholder": "​",
            "style": "IPY_MODEL_08fd0c984c8942b496f6a5b0a3858704",
            "value": "config.json: 100%"
          }
        },
        "ceeb1431ea0f4440b95d877f23193022": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_54c4e0abe6a74e39894d46ff82466af7",
            "max": 570,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_aee9912f8eb2473ebd91797272951129",
            "value": 570
          }
        },
        "5011bbcad8af434591d2dd8e407497bd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c8848eadea3e4f989f8bcb784dd15c4d",
            "placeholder": "​",
            "style": "IPY_MODEL_c8ec6468d8e04317b5670408423a204b",
            "value": " 570/570 [00:00&lt;00:00, 30.8kB/s]"
          }
        },
        "5e963a51825349e9b3f8f751026541d7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "44e577c6457d428d92a492e3c4dc5c2b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "08fd0c984c8942b496f6a5b0a3858704": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "54c4e0abe6a74e39894d46ff82466af7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "aee9912f8eb2473ebd91797272951129": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "c8848eadea3e4f989f8bcb784dd15c4d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c8ec6468d8e04317b5670408423a204b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "053e679aa2f84da89df27acf635756c3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_661656641931453bb4abc8f02871587c",
              "IPY_MODEL_3ef12a7e5aa14a259cbdb58b26b51cfa",
              "IPY_MODEL_c5bfe4d98f1448a099f9e86b5abf8a6b"
            ],
            "layout": "IPY_MODEL_8060f63ae62344d0a59c511ea10dfbc2"
          }
        },
        "661656641931453bb4abc8f02871587c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_c8821ac085994e5bb09bfa6bf462f769",
            "placeholder": "​",
            "style": "IPY_MODEL_0c3e60e4d04d4078a67d458aa0c5ab82",
            "value": "model.safetensors: 100%"
          }
        },
        "3ef12a7e5aa14a259cbdb58b26b51cfa": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2ed64aa4191742209c7e151f4edb1940",
            "max": 440449768,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_6895d0177ecf45ac9152eb45c31ad6d2",
            "value": 440449768
          }
        },
        "c5bfe4d98f1448a099f9e86b5abf8a6b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_1b2227c493554fe885e9b82ac1e44e86",
            "placeholder": "​",
            "style": "IPY_MODEL_ad2fa234879b40fda987cb0a24b8bee9",
            "value": " 440M/440M [00:02&lt;00:00, 196MB/s]"
          }
        },
        "8060f63ae62344d0a59c511ea10dfbc2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c8821ac085994e5bb09bfa6bf462f769": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "0c3e60e4d04d4078a67d458aa0c5ab82": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "2ed64aa4191742209c7e151f4edb1940": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "6895d0177ecf45ac9152eb45c31ad6d2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "1b2227c493554fe885e9b82ac1e44e86": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ad2fa234879b40fda987cb0a24b8bee9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}